1 citations · 1 across the 12 of their papers we have counts for
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Finite-Sample Inference for Sparsely Permuted Linear Regression
Hirofumi Ota, Masaaki Imaizumi
We study a linear observation model with an unknown permutation called \textit{permuted/shuffled linear regression}, where responses and covariates are mismatched and the permutati…
Minimax Rates of Estimation for Optimal Transport Map between Infinite-Dimensional Spaces
Donlapark Ponnoprat, Masaaki Imaizumi
We investigate the estimation of an optimal transport map between probability measures on an infinite-dimensional space and reveal its minimax optimal rate. Optimal transport theor…
Universality of estimators for high-dimensional linear models with block dependency
Toshiki Tsuda, Masaaki Imaizumi
We study the universality property of estimators for high-dimensional linear models, which implies that the distribution of estimators is independent of whether the covariates foll…
High-Dimensional Single-Index Models: Link Estimation and Marginal Inference
Kazuma Sawaya, Yoshimasa Uematsu, Masaaki Imaizumi
This study proposes a novel method for estimation and hypothesis testing in high-dimensional single-index models. We address a common scenario where the sample size and the dimensi…
Bayesian Analysis for Over-parameterized Linear Model via Effective Spectra
Tomoya Wakayama, Masaaki Imaizumi
In high-dimensional Bayesian statistics, various methods have been developed, including prior distributions that induce parameter sparsity to handle many parameters. Yet, these app…